An alternative design and implementation of a solid state on-load tap changer

Power quality and reliability are of great importance in the modern world, whether it be the power generated by the power utilities or the power consumed by the customer respectively. They need these supplies to be at its optimum value so that the cost is effective, and the safety of devices assured otherwise problems such as overvoltage, under-voltage, and voltage sags caused by disturbances in the power supply could be disastrous. On-load tap changers (OLTC) have therefore been used since the inception of electrical engineering. The main function of the OLTC is to change the turns of the transformer winding so that the voltage variations are limited without interrupting the secondary current.The major idea is that the electronic switches and other smart systems provide more controllability during the tap changing process, unlike mechanical switches.This paper presents an alternative design and implementation of a low-cost solid-state OLTC and employs a control strategy that is microcontroller-based, ensuring the desired flexibility and controllability required in programming the control algorithms.It eliminates the limitations of both mechanical and hybrid OLTCs (arcing, slow response time, losses) and is user-friendly (provides an effective communication medium). Voltage regulation is achieved by varying the turns of the transformer winding whiles it is energized, supplying load current and with the tap selection carried out on the primary side. Therefore, this approach provides a less expensive system but ensures the efficiency and reliability of voltage regulation.

Detection of Winding Axial Displacement of a Real Transformer by Frequency Response Analysis without Fingerprint Data

Detection of the axial displacement of power-transformer winding is important to ensure its highly reliable operation. Frequency response analysis is a promising candidate in detecting the axial displacement. However, a method of detecting the axial displacement at an incipient stage without the need for fingerprint data has not been investigated yet. This paper focuses on resonances showing a bipolar signature in the transfer function of inductive interwinding measurement, which is sensitive to the axial displacement of the winding. Transfer functions in the inductive interwinding measurements of eight power transformers are measured before shipping to elucidate the features of resonances showing a bipolar signature. The measured resonances showing the bipolar signature can be divided into the “stair type” and the “crossing-curve type”. It is found that the grounding points in an inductive interwinding measurement determine the type of resonance showing the bipolar signature, irrespective of the type of winding, such as interleaved or multilayer winding, the winding arrangement, and the existence of stabilizing and tertiary windings. On the basis of this finding, a method of detecting the axial displacement of a transformer winding is proposed. In the proposed method, the amplitudes of the resonances among three phases are compared, or the three-phase pattern of the resonances is compared with normal patterns. Therefore, the proposed method is applicable to three-phase transformers without fingerprint data. The proposed method is applied to a real transformer that experienced a ground fault due to a lightning strike at a nearby transmission tower, and the effectiveness of the proposed method is confirmed.

Influence of HVDC Transmission on DC Bias of AC Grid and Its Treatment

With the rapid development of China’s electric power industry, the high-voltage and long-distance direct current (DC) transmission effectively solved the problem of uneven power distribution. When the high voltage direct current transmission is in unipolar operation or bipolar asymmetric operation, part of the DC current will flow into the transformer winding through the grounded neutral point, which will cause the DC bias problem. This article used CDEGS software for modeling, and introduced the process of CDEGS software for DC bias simulation modeling. In this paper, the DC bias model of regional power grid is first established, based on the Zhejiang power grid topology and the test soil resistivity date. Then the DC bias currents of the transformers are calculated, and finally the corresponding treatment measures are proposed. According to the governance measures, this article adjusted the simulation model. The calculation results show that the treatment measures have good effects, which can provide an important reference for the future treatment of transformer DC bias.

Comparison of Machine Learning Algorithms for the Prediction of Mechanical Stress in Three-Phase Power Transformer Winding Conductors

This research compares four machine learning techniques: linear regression, support vector regression, random forests, and artificial neural networks, with regard to the determination of mechanical stress in power transformer winding conductors due to three-phase electrical faults. The accuracy compared with finite element results was evaluated for each model. The input data were the transient electrical fault currents of power system equivalents with impedances from low to high values. The output data were the mechanical stress in the conductors located in the middle of the winding. To simplify the design, only one hyperparameter was varied on each machine learning technique. The random forests technique had the most accurate results. The highest errors were found for low-stress values, mainly due to the high difference between maximum and minimum stresses, which made the training of the machine learning models difficult. In the end, an accurate model that could be used in the continuous monitoring of mechanical stress was obtained.

Research on On-Line Detection Method of Transformer Winding Deformation Based on VFTO

At present, the detection of transformer winding deformation faults is carried out in an offline state, which requires the transformer to cooperate with the implementation of planned power outages, or it takes place after the sudden failure of the transformer when it is out of operation. It is difficult to obtain the status information of the windings online in time. Since the transformer will suffer very fast transient overvoltage (VFTO) impact during operation, combined with the principle of the frequency response method, an online detection method of transformer winding deformation based on VFTO is proposed. In order to study the frequency response characteristics of transformer winding under the impact of VFTO, the generation process of VFTO is simulated by simulation software, and the equivalent circuit model of transformer winding before and after deformation is established. The VFTO signal is injected into the transformer circuit model as an excitation source, and the changes of resonant frequencies of frequency response curve under different deformation types and different deformation degrees of winding are analyzed. The simulation results show that the frequency response curves of different winding deformation types are different. Different deformation degrees are simulated by increasing the radial capacitance by 4%, 13%, and 23%, series inductance by 2%, 4%, and 6%, and longitudinal capacitance by 3%, 6%, and 9%, and the change of resonance frequencies can comprehensively reflect the deformation information of winding. At the same time, the tests of different deformation types and deformation degrees of the simulated winding are carried out. The results show that with the deepening of the change degree of the simulated fault inductance value, the frequency response curve shifts to the low-frequency direction, confirming the feasibility of the online detection method of transformer winding deformation based on VFTO.